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dc.contributor.authorTarrant, Jeanne
dc.contributor.authorArmstrong, Adrian J.
dc.identifier.citationArmstrong, A.J. & Tarrant, J. 2013. Using predictive modelling to guide the conservation of a critically endangered coastal wetland amphibian. Journal for nature conservation. 21(5):369-381. []en_US
dc.description.abstractAmphibians are the most threatened Class of vertebrate, with wetland-associated anurans in particularsuffering high levels of habitat loss. We used predictive modelling to better understand the distribution ofa critically endangered South African endemic (Hyperolius pickersgilli) and to guide conservation action.MaxEnt distribution models were produced based on limited occurrence data. Predicted localities withprobability of occurrence ≥60% were surveyed. Ten new sub-populations were discovered. The meanprobability of occurrence for the species at wetlands where it was detected was greater than that atwetlands where it was not detected or absent. In addition, 17 known historical localities were re-visitedand the species deemed absent at 8 of these. The total number of localities at which the species is nowknown to occur is 18, which is an increase in the known extant sub-populations of six. We recalculate thearea of occupancy and extent of occurrence for the species as 108 km2and 2081.5 km2, respectively; bothincreases on previous estimates. Implications of these changes on the IUCN Red List status of H. pickersgilliare discussed. A friction map was created to identify possible linkages between sub-populations, whichcan be used to guide habitat restoration and population repatriation. Given the degree of isolation ofsubpopulations and the potentially severe threats to most of these, urgent conservation action for H.pickersgilli remains crucial. This study provides a method for use in conservation planning for wetland-breeding amphibians in eastern coastal regions of Africa and elsewhere.en_US
dc.subjectcoastal wetlandsen_US
dc.subjectred-list statusen_US
dc.subjectSouth Africaen_US
dc.titleUsing predictive modelling to guide the conservation of a critically endangered coastal wetland amphibianen_US

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